首页|Image Fusion Based on the Self-Organizing Feature Map Neural Networks
Image Fusion Based on the Self-Organizing Feature Map Neural Networks
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
万方数据
This paper presents a new image datafusion scheme based on the self-organizing featuremap (SOFM) neural networks.The scheme consists ofthree steps:(1) pre-processing of the images,whereweighted median filtering removes part of the noisecomponents corrupting the image,(2) pixel clusteringfor each image using two-dimensional self-organizingfeature map neural networks,and (3) fusion of the im-ages obtained in Step (2) utilizing fuzzy logic,whichsuppresses the residual noise components and thusfurther improves the image quality.It proves thatsuch a three-step combination offers an impressive ef-fectiveness and performance improvement,which isconfirmed by simulations involving three image sen-sors (each of which has a different noise structure).
Image data fusionMedian filterSelf-organizing feature map neural network
Zhang Zhaoli、SUN Shenghe
展开 >
Automatic Test and Control Department,Harbin Institute of Technology,Harbin 150001,China
NETL
NSTL
万方数据
